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Numerical Variables

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In this course, you will learn how to apply basic and more advanced feature engineering to tabular data with python, during this course,  we will see a range of different techniques and methods to handle many common cases within the data set, so in result, you will create great features so that your machine learning models can predict good results.

Feature Engineering with Python

## Definition
When scaling variables to the median and quantiles, the median value is removed from the observations, and the result is divided by the inter-quartile range (IQR). 

The IQR is the range between the first quartile and the third quartile, or, in other words, the range between the 25th quantile and the 75th quantile. It can be calculated with the following formula:

$$\bar{x} = \frac{X - median(X)}{75th \space quantile(X) - 25th \space quantile(X) }$$

# Definition
When scaling variables to the median and quantiles, the median value is removed from the observations, and the result is divided by the inter-quartile range (IQR). 

The IQR is the range between the first quartile and the third quartile, or, in other words, the range between the 25th quantile and the 75th quantile. It can be calculated with the following formula:

This lesson aims to illustrate a feature scaling method called robust scaling, also known as scaling to median and IQR. We will see the formula of this method, some points to consider, and of course, the python code to use robust scaling to reduce the scale of your features.


Robust scaling (scaling to median and IQR)

This lesson aims to illustrate a feature scaling method called robust scaling, also known as scaling to median and IQR. We will see the formula of this method, some points to consider, and of course, the python code to use robust scaling to reduce the scale of your features.

Introduction

Variable Types

Common Concerns in Datasets

Handling & Imputing Missing Values

Encoding Categorical Variables

Transforming Variables

Variable Discretization

Handling Outliers

Feature Scaling

Engineering Geospatial Data

Handling Date-Time and Mixed Variables

Resampling Imbalanced Data

Advanced Feature Engineering Techniques

Conclusion

Robust scaling (scaling to median and IQR)

Definition